Overview

Dataset statistics

Number of variables15
Number of observations376752
Missing cells738484
Missing cells (%)13.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.5 MiB
Average record size in memory121.0 B

Variable types

Text13
Categorical1
Boolean1

Alerts

Pool is highly imbalanced (50.9%)Imbalance
status has 39872 (10.6%) missing valuesMissing
propertyType has 34669 (9.2%) missing valuesMissing
baths has 106051 (28.1%) missing valuesMissing
fireplace has 273656 (72.6%) missing valuesMissing
sqft has 40427 (10.7%) missing valuesMissing
beds has 90995 (24.2%) missing valuesMissing
stories has 150340 (39.9%) missing valuesMissing

Reproduction

Analysis started2024-05-28 12:46:13.159114
Analysis finished2024-05-28 12:48:18.713863
Duration2 minutes and 5.55 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

status
Text

MISSING 

Distinct159
Distinct (%)< 0.1%
Missing39872
Missing (%)10.6%
Memory size5.7 MiB
2024-05-28T12:48:19.012091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length38
Median length8
Mean length7.8415994
Min length1

Characters and Unicode

Total characters2641678
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)< 0.1%

Sample

1st rowActive
2nd rowfor sale
3rd rowfor sale
4th rowfor sale
5th rowfor sale
ValueCountFrequency (%)
for 199834
35.8%
sale 199485
35.8%
active 106321
19.1%
foreclosure 6765
 
1.2%
new 6163
 
1.1%
construction 5473
 
1.0%
pending 5357
 
1.0%
contract 3799
 
0.7%
pre-foreclosure 3679
 
0.7%
under 3658
 
0.7%
Other values (125) 16996
 
3.0%
2024-05-28T12:48:20.070091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 351092
13.3%
o 244611
9.3%
r 239333
9.1%
223230
8.5%
s 216954
8.2%
l 211027
8.0%
a 207394
7.9%
f 166625
 
6.3%
c 137169
 
5.2%
t 131799
 
5.0%
Other values (52) 512444
19.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2641678
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 351092
13.3%
o 244611
9.3%
r 239333
9.1%
223230
8.5%
s 216954
8.2%
l 211027
8.0%
a 207394
7.9%
f 166625
 
6.3%
c 137169
 
5.2%
t 131799
 
5.0%
Other values (52) 512444
19.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2641678
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 351092
13.3%
o 244611
9.3%
r 239333
9.1%
223230
8.5%
s 216954
8.2%
l 211027
8.0%
a 207394
7.9%
f 166625
 
6.3%
c 137169
 
5.2%
t 131799
 
5.0%
Other values (52) 512444
19.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2641678
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 351092
13.3%
o 244611
9.3%
r 239333
9.1%
223230
8.5%
s 216954
8.2%
l 211027
8.0%
a 207394
7.9%
f 166625
 
6.3%
c 137169
 
5.2%
t 131799
 
5.0%
Other values (52) 512444
19.4%

propertyType
Text

MISSING 

Distinct1280
Distinct (%)0.4%
Missing34669
Missing (%)9.2%
Memory size5.7 MiB
2024-05-28T12:48:20.890317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length129
Median length112
Mean length13.526688
Min length1

Characters and Unicode

Total characters4627250
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique615 ?
Unique (%)0.2%

Sample

1st rowSingle Family Home
2nd rowsingle-family home
3rd rowsingle-family home
4th rowsingle-family home
5th rowlot/land
ValueCountFrequency (%)
home 126812
21.0%
single 97954
16.2%
family 97331
16.1%
single-family 92172
15.2%
condo 42515
 
7.0%
lot/land 20470
 
3.4%
townhouse 18559
 
3.1%
land 10795
 
1.8%
traditional 9679
 
1.6%
multi-family 9422
 
1.6%
Other values (277) 79430
13.1%
2024-05-28T12:48:22.350846image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 464854
 
10.0%
i 440973
 
9.5%
e 398240
 
8.6%
o 376263
 
8.1%
m 361250
 
7.8%
n 336130
 
7.3%
a 282822
 
6.1%
263304
 
5.7%
y 210501
 
4.5%
g 193385
 
4.2%
Other values (58) 1299528
28.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4627250
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 464854
 
10.0%
i 440973
 
9.5%
e 398240
 
8.6%
o 376263
 
8.1%
m 361250
 
7.8%
n 336130
 
7.3%
a 282822
 
6.1%
263304
 
5.7%
y 210501
 
4.5%
g 193385
 
4.2%
Other values (58) 1299528
28.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4627250
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 464854
 
10.0%
i 440973
 
9.5%
e 398240
 
8.6%
o 376263
 
8.1%
m 361250
 
7.8%
n 336130
 
7.3%
a 282822
 
6.1%
263304
 
5.7%
y 210501
 
4.5%
g 193385
 
4.2%
Other values (58) 1299528
28.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4627250
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 464854
 
10.0%
i 440973
 
9.5%
e 398240
 
8.6%
o 376263
 
8.1%
m 361250
 
7.8%
n 336130
 
7.3%
a 282822
 
6.1%
263304
 
5.7%
y 210501
 
4.5%
g 193385
 
4.2%
Other values (58) 1299528
28.1%

street
Text

Distinct337041
Distinct (%)89.5%
Missing2
Missing (%)< 0.1%
Memory size5.7 MiB
2024-05-28T12:48:23.076241image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length96
Median length83
Mean length18.584337
Min length1

Characters and Unicode

Total characters7001649
Distinct characters87
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique303080 ?
Unique (%)80.4%

Sample

1st row240 Heather Ln
2nd row12911 E Heroy Ave
3rd row2005 Westridge Rd
4th row4311 Livingston Ave
5th row1524 Kiscoe St
ValueCountFrequency (%)
st 83379
 
5.7%
dr 64466
 
4.4%
ave 62428
 
4.2%
rd 32574
 
2.2%
ln 22982
 
1.6%
n 18911
 
1.3%
w 18424
 
1.3%
ct 17805
 
1.2%
s 17710
 
1.2%
sw 15596
 
1.1%
Other values (69377) 1115547
75.9%
2024-05-28T12:48:24.096233image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1154167
 
16.5%
e 357725
 
5.1%
1 338317
 
4.8%
r 287201
 
4.1%
t 285306
 
4.1%
a 268927
 
3.8%
n 248355
 
3.5%
0 231923
 
3.3%
2 222042
 
3.2%
l 208859
 
3.0%
Other values (77) 3398827
48.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7001649
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1154167
 
16.5%
e 357725
 
5.1%
1 338317
 
4.8%
r 287201
 
4.1%
t 285306
 
4.1%
a 268927
 
3.8%
n 248355
 
3.5%
0 231923
 
3.3%
2 222042
 
3.2%
l 208859
 
3.0%
Other values (77) 3398827
48.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7001649
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1154167
 
16.5%
e 357725
 
5.1%
1 338317
 
4.8%
r 287201
 
4.1%
t 285306
 
4.1%
a 268927
 
3.8%
n 248355
 
3.5%
0 231923
 
3.3%
2 222042
 
3.2%
l 208859
 
3.0%
Other values (77) 3398827
48.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7001649
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1154167
 
16.5%
e 357725
 
5.1%
1 338317
 
4.8%
r 287201
 
4.1%
t 285306
 
4.1%
a 268927
 
3.8%
n 248355
 
3.5%
0 231923
 
3.3%
2 222042
 
3.2%
l 208859
 
3.0%
Other values (77) 3398827
48.5%

baths
Text

MISSING 

Distinct229
Distinct (%)0.1%
Missing106051
Missing (%)28.1%
Memory size5.7 MiB
2024-05-28T12:48:24.452777image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length21
Median length19
Mean length5.4122408
Min length1

Characters and Unicode

Total characters1465099
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)< 0.1%

Sample

1st row3.5
2nd row3 Baths
3rd row2 Baths
4th row8 Baths
5th row2
ValueCountFrequency (%)
baths 121226
28.7%
2 85093
20.2%
3 54107
12.8%
bathrooms 23280
 
5.5%
4 21441
 
5.1%
2.0 16570
 
3.9%
2.5 12875
 
3.0%
3.0 10867
 
2.6%
1 10577
 
2.5%
5 7664
 
1.8%
Other values (128) 58488
13.9%
2024-05-28T12:48:25.128957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
151689
10.4%
a 151131
10.3%
t 144708
9.9%
s 144506
9.9%
h 144506
9.9%
B 143990
9.8%
2 122665
8.4%
0 74457
 
5.1%
3 72933
 
5.0%
. 64720
 
4.4%
Other values (25) 249794
17.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1465099
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
151689
10.4%
a 151131
10.3%
t 144708
9.9%
s 144506
9.9%
h 144506
9.9%
B 143990
9.8%
2 122665
8.4%
0 74457
 
5.1%
3 72933
 
5.0%
. 64720
 
4.4%
Other values (25) 249794
17.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1465099
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
151689
10.4%
a 151131
10.3%
t 144708
9.9%
s 144506
9.9%
h 144506
9.9%
B 143990
9.8%
2 122665
8.4%
0 74457
 
5.1%
3 72933
 
5.0%
. 64720
 
4.4%
Other values (25) 249794
17.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1465099
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
151689
10.4%
a 151131
10.3%
t 144708
9.9%
s 144506
9.9%
h 144506
9.9%
B 143990
9.8%
2 122665
8.4%
0 74457
 
5.1%
3 72933
 
5.0%
. 64720
 
4.4%
Other values (25) 249794
17.0%
Distinct320982
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size5.7 MiB
2024-05-28T12:48:25.805733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length840
Median length605
Mean length374.53993
Min length334

Characters and Unicode

Total characters141108669
Distinct characters86
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique311098 ?
Unique (%)82.6%

Sample

1st row{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Central A/C, Heat Pump', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': None, 'factLabel': 'lotsize'}, {'factValue': '$144', 'factLabel': 'Price/sqft'}]}
2nd row{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '5828 sqft', 'factLabel': 'lotsize'}, {'factValue': '$159/sqft', 'factLabel': 'Price/sqft'}]}
3rd row{'atAGlanceFacts': [{'factValue': '1961', 'factLabel': 'Year built'}, {'factValue': '1967', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Attached Garage', 'factLabel': 'Parking'}, {'factValue': '8,626 sqft', 'factLabel': 'lotsize'}, {'factValue': '$965/sqft', 'factLabel': 'Price/sqft'}]}
4th row{'atAGlanceFacts': [{'factValue': '2006', 'factLabel': 'Year built'}, {'factValue': '2006', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Detached Garage', 'factLabel': 'Parking'}, {'factValue': '8,220 sqft', 'factLabel': 'lotsize'}, {'factValue': '$371/sqft', 'factLabel': 'Price/sqft'}]}
5th row{'atAGlanceFacts': [{'factValue': '', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '10,019 sqft', 'factLabel': 'lotsize'}, {'factValue': None, 'factLabel': 'Price/sqft'}]}
ValueCountFrequency (%)
factvalue 2637264
20.7%
factlabel 2637264
20.7%
755514
 
5.9%
year 753504
 
5.9%
cooling 390526
 
3.1%
heating 388831
 
3.1%
parking 383242
 
3.0%
price/sqft 376752
 
3.0%
lotsize 376752
 
3.0%
ataglancefacts 376752
 
3.0%
Other values (29468) 3666405
28.8%
2024-05-28T12:48:26.831873image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 21596609
15.3%
a 14167741
 
10.0%
12366058
 
8.8%
e 9761308
 
6.9%
t 8585932
 
6.1%
l 7525354
 
5.3%
c 6883192
 
4.9%
f 5953749
 
4.2%
: 5651296
 
4.0%
, 5121183
 
3.6%
Other values (76) 43496247
30.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 141108669
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
' 21596609
15.3%
a 14167741
 
10.0%
12366058
 
8.8%
e 9761308
 
6.9%
t 8585932
 
6.1%
l 7525354
 
5.3%
c 6883192
 
4.9%
f 5953749
 
4.2%
: 5651296
 
4.0%
, 5121183
 
3.6%
Other values (76) 43496247
30.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 141108669
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
' 21596609
15.3%
a 14167741
 
10.0%
12366058
 
8.8%
e 9761308
 
6.9%
t 8585932
 
6.1%
l 7525354
 
5.3%
c 6883192
 
4.9%
f 5953749
 
4.2%
: 5651296
 
4.0%
, 5121183
 
3.6%
Other values (76) 43496247
30.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 141108669
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
' 21596609
15.3%
a 14167741
 
10.0%
12366058
 
8.8%
e 9761308
 
6.9%
t 8585932
 
6.1%
l 7525354
 
5.3%
c 6883192
 
4.9%
f 5953749
 
4.2%
: 5651296
 
4.0%
, 5121183
 
3.6%
Other values (76) 43496247
30.8%

fireplace
Text

MISSING 

Distinct1652
Distinct (%)1.6%
Missing273656
Missing (%)72.6%
Memory size5.7 MiB
2024-05-28T12:48:27.349038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length231
Median length3
Mean length5.0308547
Min length1

Characters and Unicode

Total characters518661
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1038 ?
Unique (%)1.0%

Sample

1st rowGas Logs
2nd rowyes
3rd rowyes
4th rowyes
5th rowYes
ValueCountFrequency (%)
yes 71196
53.6%
1 15302
 
11.5%
room 3325
 
2.5%
fireplace 3304
 
2.5%
gas 3127
 
2.4%
2 2535
 
1.9%
not 1993
 
1.5%
applicable 1993
 
1.5%
closets 1725
 
1.3%
wood 1710
 
1.3%
Other values (350) 26724
 
20.1%
2024-05-28T12:48:28.173525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 93103
18.0%
s 81939
15.8%
y 52241
 
10.1%
29838
 
5.8%
Y 21802
 
4.2%
o 21186
 
4.1%
i 18735
 
3.6%
a 18442
 
3.6%
1 15313
 
3.0%
l 15193
 
2.9%
Other values (59) 150869
29.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 518661
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 93103
18.0%
s 81939
15.8%
y 52241
 
10.1%
29838
 
5.8%
Y 21802
 
4.2%
o 21186
 
4.1%
i 18735
 
3.6%
a 18442
 
3.6%
1 15313
 
3.0%
l 15193
 
2.9%
Other values (59) 150869
29.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 518661
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 93103
18.0%
s 81939
15.8%
y 52241
 
10.1%
29838
 
5.8%
Y 21802
 
4.2%
o 21186
 
4.1%
i 18735
 
3.6%
a 18442
 
3.6%
1 15313
 
3.0%
l 15193
 
2.9%
Other values (59) 150869
29.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 518661
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 93103
18.0%
s 81939
15.8%
y 52241
 
10.1%
29838
 
5.8%
Y 21802
 
4.2%
o 21186
 
4.1%
i 18735
 
3.6%
a 18442
 
3.6%
1 15313
 
3.0%
l 15193
 
2.9%
Other values (59) 150869
29.1%

city
Text

Distinct2026
Distinct (%)0.5%
Missing31
Missing (%)< 0.1%
Memory size5.7 MiB
2024-05-28T12:48:28.646347image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length38
Median length29
Mean length8.9983303
Min length1

Characters and Unicode

Total characters3389860
Distinct characters60
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique435 ?
Unique (%)0.1%

Sample

1st rowSouthern Pines
2nd rowSpokane Valley
3rd rowLos Angeles
4th rowDallas
5th rowPalm Bay
ValueCountFrequency (%)
houston 24443
 
4.9%
miami 20769
 
4.1%
san 19389
 
3.8%
antonio 15580
 
3.1%
fort 11458
 
2.3%
jacksonville 10360
 
2.1%
charlotte 9688
 
1.9%
dallas 8855
 
1.8%
beach 8779
 
1.7%
brooklyn 7288
 
1.4%
Other values (1701) 367265
72.9%
2024-05-28T12:48:29.450090image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 342833
 
10.1%
o 283525
 
8.4%
n 256799
 
7.6%
e 247775
 
7.3%
l 224065
 
6.6%
i 218806
 
6.5%
t 194310
 
5.7%
s 159635
 
4.7%
r 151103
 
4.5%
127193
 
3.8%
Other values (50) 1183816
34.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3389860
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 342833
 
10.1%
o 283525
 
8.4%
n 256799
 
7.6%
e 247775
 
7.3%
l 224065
 
6.6%
i 218806
 
6.5%
t 194310
 
5.7%
s 159635
 
4.7%
r 151103
 
4.5%
127193
 
3.8%
Other values (50) 1183816
34.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3389860
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 342833
 
10.1%
o 283525
 
8.4%
n 256799
 
7.6%
e 247775
 
7.3%
l 224065
 
6.6%
i 218806
 
6.5%
t 194310
 
5.7%
s 159635
 
4.7%
r 151103
 
4.5%
127193
 
3.8%
Other values (50) 1183816
34.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3389860
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 342833
 
10.1%
o 283525
 
8.4%
n 256799
 
7.6%
e 247775
 
7.3%
l 224065
 
6.6%
i 218806
 
6.5%
t 194310
 
5.7%
s 159635
 
4.7%
r 151103
 
4.5%
127193
 
3.8%
Other values (50) 1183816
34.9%
Distinct297283
Distinct (%)78.9%
Missing0
Missing (%)0.0%
Memory size5.7 MiB
2024-05-28T12:48:30.099220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3688
Median length3289
Mean length301.93602
Min length68

Characters and Unicode

Total characters113755000
Distinct characters84
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique265952 ?
Unique (%)70.6%

Sample

1st row[{'rating': ['4', '4', '7', 'NR', '4', '7', 'NR', 'NR'], 'data': {'Distance': ['2.7 mi', '3.6 mi', '5.1 mi', '4.0 mi', '10.5 mi', '12.6 mi', '2.7 mi', '3.1 mi'], 'Grades': ['3–5', '6–8', '9–12', 'PK–2', '6–8', '9–12', 'PK–5', 'K–12']}, 'name': ['Southern Pines Elementary School', 'Southern Middle School', 'Pinecrest High School', 'Southern Pines Primary School', "Crain's Creek Middle School", 'Union Pines High School', 'Episcopal Day Private School', 'Calvary Christian Private School']}]
2nd row[{'rating': ['4/10', 'None/10', '4/10'], 'data': {'Distance': ['1.65mi', '1.32mi', '1.01mi'], 'Grades': ['9-12', '3-8', 'PK-8']}, 'name': ['East Valley High School&Extension', 'Eastvalley Middle School', 'Trentwood Elementary School']}]
3rd row[{'rating': ['8/10', '4/10', '8/10'], 'data': {'Distance': ['1.19mi', '2.06mi', '2.63mi'], 'Grades': ['6-8', 'K-5', '9-12']}, 'name': ['Paul Revere Middle School', 'Brentwood Science School', 'Palisades Charter High School']}]
4th row[{'rating': ['9/10', '9/10', '10/10', '9/10'], 'data': {'Distance': ['1.05mi', '0.1mi', '1.05mi', '0.81mi'], 'Grades': ['5-6', 'PK-4', '7-8', '9-12']}, 'name': ['Mcculloch Intermediate School', 'Bradfield Elementary School', 'Highland Park Middle School', 'Highland Park High School']}]
5th row[{'rating': ['4/10', '5/10', '5/10'], 'data': {'Distance': ['5.96mi', '3.25mi', '3.03mi'], 'Grades': ['7-8', '9-12', 'PK-6']}, 'name': ['Southwest Middle School', 'Bayside High School', 'Westside Elementary School']}]
ValueCountFrequency (%)
school 1412391
 
9.8%
mi 905584
 
6.3%
elementary 446129
 
3.1%
high 438137
 
3.0%
name 376922
 
2.6%
grades 376855
 
2.6%
rating 376752
 
2.6%
data 376752
 
2.6%
distance 376752
 
2.6%
middle 322027
 
2.2%
Other values (16026) 9073783
62.7%
2024-05-28T12:48:31.070799image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 16729704
 
14.7%
14109739
 
12.4%
, 6130940
 
5.4%
e 4771667
 
4.2%
o 4677472
 
4.1%
a 4597896
 
4.0%
i 4515190
 
4.0%
l 3309791
 
2.9%
t 3115470
 
2.7%
n 3057910
 
2.7%
Other values (74) 48739221
42.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 113755000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
' 16729704
 
14.7%
14109739
 
12.4%
, 6130940
 
5.4%
e 4771667
 
4.2%
o 4677472
 
4.1%
a 4597896
 
4.0%
i 4515190
 
4.0%
l 3309791
 
2.9%
t 3115470
 
2.7%
n 3057910
 
2.7%
Other values (74) 48739221
42.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 113755000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
' 16729704
 
14.7%
14109739
 
12.4%
, 6130940
 
5.4%
e 4771667
 
4.2%
o 4677472
 
4.1%
a 4597896
 
4.0%
i 4515190
 
4.0%
l 3309791
 
2.9%
t 3115470
 
2.7%
n 3057910
 
2.7%
Other values (74) 48739221
42.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 113755000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
' 16729704
 
14.7%
14109739
 
12.4%
, 6130940
 
5.4%
e 4771667
 
4.2%
o 4677472
 
4.1%
a 4597896
 
4.0%
i 4515190
 
4.0%
l 3309791
 
2.9%
t 3115470
 
2.7%
n 3057910
 
2.7%
Other values (74) 48739221
42.8%

sqft
Text

MISSING 

Distinct25405
Distinct (%)7.6%
Missing40427
Missing (%)10.7%
Memory size5.7 MiB
2024-05-28T12:48:31.718127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length41
Median length40
Mean length9.3043604
Min length1

Characters and Unicode

Total characters3129289
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7326 ?
Unique (%)2.2%

Sample

1st row2900
2nd row1,947 sqft
3rd row3,000 sqft
4th row6,457 sqft
5th row897 sqft
ValueCountFrequency (%)
sqft 182670
29.8%
interior 23677
 
3.9%
total 23677
 
3.9%
livable 23677
 
3.9%
area 23677
 
3.9%
0 11710
 
1.9%
1,200 1298
 
0.2%
1,000 955
 
0.2%
1,500 909
 
0.1%
1,100 879
 
0.1%
Other values (14448) 320574
52.2%
2024-05-28T12:48:33.052678image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
277378
 
8.9%
, 253013
 
8.1%
1 232407
 
7.4%
t 230024
 
7.4%
2 184859
 
5.9%
s 182670
 
5.8%
q 182670
 
5.8%
f 182670
 
5.8%
0 170039
 
5.4%
3 115271
 
3.7%
Other values (18) 1118288
35.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3129289
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
277378
 
8.9%
, 253013
 
8.1%
1 232407
 
7.4%
t 230024
 
7.4%
2 184859
 
5.9%
s 182670
 
5.8%
q 182670
 
5.8%
f 182670
 
5.8%
0 170039
 
5.4%
3 115271
 
3.7%
Other values (18) 1118288
35.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3129289
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
277378
 
8.9%
, 253013
 
8.1%
1 232407
 
7.4%
t 230024
 
7.4%
2 184859
 
5.9%
s 182670
 
5.8%
q 182670
 
5.8%
f 182670
 
5.8%
0 170039
 
5.4%
3 115271
 
3.7%
Other values (18) 1118288
35.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3129289
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
277378
 
8.9%
, 253013
 
8.1%
1 232407
 
7.4%
t 230024
 
7.4%
2 184859
 
5.9%
s 182670
 
5.8%
q 182670
 
5.8%
f 182670
 
5.8%
0 170039
 
5.4%
3 115271
 
3.7%
Other values (18) 1118288
35.7%
Distinct4549
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size5.7 MiB
2024-05-28T12:48:33.883818image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.9980783
Min length1

Characters and Unicode

Total characters1883036
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique598 ?
Unique (%)0.2%

Sample

1st row28387
2nd row99216
3rd row90049
4th row75205
5th row32908
ValueCountFrequency (%)
32137 2139
 
0.6%
33131 1562
 
0.4%
34747 1486
 
0.4%
78245 1390
 
0.4%
34759 1331
 
0.4%
33132 1328
 
0.4%
33137 1308
 
0.3%
78253 1281
 
0.3%
78254 1238
 
0.3%
33130 1168
 
0.3%
Other values (4539) 362521
96.2%
2024-05-28T12:48:35.153673image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 335725
17.8%
1 233374
12.4%
2 233220
12.4%
7 230263
12.2%
0 221080
11.7%
4 151316
8.0%
8 148045
7.9%
9 120809
 
6.4%
6 104944
 
5.6%
5 104016
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1883036
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 335725
17.8%
1 233374
12.4%
2 233220
12.4%
7 230263
12.2%
0 221080
11.7%
4 151316
8.0%
8 148045
7.9%
9 120809
 
6.4%
6 104944
 
5.6%
5 104016
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1883036
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 335725
17.8%
1 233374
12.4%
2 233220
12.4%
7 230263
12.2%
0 221080
11.7%
4 151316
8.0%
8 148045
7.9%
9 120809
 
6.4%
6 104944
 
5.6%
5 104016
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1883036
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 335725
17.8%
1 233374
12.4%
2 233220
12.4%
7 230263
12.2%
0 221080
11.7%
4 151316
8.0%
8 148045
7.9%
9 120809
 
6.4%
6 104944
 
5.6%
5 104016
 
5.5%

beds
Text

MISSING 

Distinct1184
Distinct (%)0.4%
Missing90995
Missing (%)24.2%
Memory size5.7 MiB
2024-05-28T12:48:35.660429image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length122
Median length121
Mean length4.1197206
Min length1

Characters and Unicode

Total characters1177239
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique716 ?
Unique (%)0.3%

Sample

1st row4
2nd row3 Beds
3rd row3 Beds
4th row5 Beds
5th row2 Beds
ValueCountFrequency (%)
beds 133134
29.3%
3 97706
21.5%
4 63690
14.0%
2 47706
 
10.5%
bd 32126
 
7.1%
5 20327
 
4.5%
baths 15278
 
3.4%
3.0 8078
 
1.8%
6 6274
 
1.4%
1 5743
 
1.3%
Other values (1126) 23684
 
5.2%
2024-05-28T12:48:36.944345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
168891
14.3%
d 165275
14.0%
s 151465
12.9%
B 149166
12.7%
e 134832
11.5%
3 106681
9.1%
4 69930
5.9%
2 51357
 
4.4%
b 32130
 
2.7%
5 22774
 
1.9%
Other values (46) 124738
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1177239
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
168891
14.3%
d 165275
14.0%
s 151465
12.9%
B 149166
12.7%
e 134832
11.5%
3 106681
9.1%
4 69930
5.9%
2 51357
 
4.4%
b 32130
 
2.7%
5 22774
 
1.9%
Other values (46) 124738
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1177239
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
168891
14.3%
d 165275
14.0%
s 151465
12.9%
B 149166
12.7%
e 134832
11.5%
3 106681
9.1%
4 69930
5.9%
2 51357
 
4.4%
b 32130
 
2.7%
5 22774
 
1.9%
Other values (46) 124738
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1177239
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
168891
14.3%
d 165275
14.0%
s 151465
12.9%
B 149166
12.7%
e 134832
11.5%
3 106681
9.1%
4 69930
5.9%
2 51357
 
4.4%
b 32130
 
2.7%
5 22774
 
1.9%
Other values (46) 124738
10.6%

state
Categorical

Distinct39
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.7 MiB
FL
115303 
TX
83705 
NY
24455 
CA
23379 
NC
21829 
Other values (34)
108081 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters753504
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowNC
2nd rowWA
3rd rowCA
4th rowTX
5th rowFL

Common Values

ValueCountFrequency (%)
FL 115303
30.6%
TX 83705
22.2%
NY 24455
 
6.5%
CA 23379
 
6.2%
NC 21829
 
5.8%
TN 18327
 
4.9%
WA 13798
 
3.7%
OH 12550
 
3.3%
IL 8935
 
2.4%
NV 8481
 
2.3%
Other values (29) 45990
 
12.2%

Length

2024-05-28T12:48:37.288334image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
fl 115304
30.6%
tx 83705
22.2%
ny 24455
 
6.5%
ca 23379
 
6.2%
nc 21829
 
5.8%
tn 18327
 
4.9%
wa 13798
 
3.7%
oh 12550
 
3.3%
il 8935
 
2.4%
nv 8481
 
2.3%
Other values (28) 45989
 
12.2%

Most occurring characters

ValueCountFrequency (%)
L 124239
16.5%
F 115304
15.3%
T 104227
13.8%
X 83705
11.1%
N 76850
10.2%
C 56306
7.5%
A 55317
7.3%
Y 24545
 
3.3%
O 22654
 
3.0%
I 18111
 
2.4%
Other values (16) 72246
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 753504
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
L 124239
16.5%
F 115304
15.3%
T 104227
13.8%
X 83705
11.1%
N 76850
10.2%
C 56306
7.5%
A 55317
7.3%
Y 24545
 
3.3%
O 22654
 
3.0%
I 18111
 
2.4%
Other values (16) 72246
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 753504
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
L 124239
16.5%
F 115304
15.3%
T 104227
13.8%
X 83705
11.1%
N 76850
10.2%
C 56306
7.5%
A 55317
7.3%
Y 24545
 
3.3%
O 22654
 
3.0%
I 18111
 
2.4%
Other values (16) 72246
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 753504
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
L 124239
16.5%
F 115304
15.3%
T 104227
13.8%
X 83705
11.1%
N 76850
10.2%
C 56306
7.5%
A 55317
7.3%
Y 24545
 
3.3%
O 22654
 
3.0%
I 18111
 
2.4%
Other values (16) 72246
9.6%

stories
Text

MISSING 

Distinct347
Distinct (%)0.2%
Missing150340
Missing (%)39.9%
Memory size5.7 MiB
2024-05-28T12:48:37.864161image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length3
Mean length2.8525299
Min length1

Characters and Unicode

Total characters645847
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)< 0.1%

Sample

1st row2.0
2nd row1.0
3rd row3.0
4th row2.0
5th rowOne
ValueCountFrequency (%)
1.0 67435
28.5%
2.0 55275
23.4%
1 24824
 
10.5%
2 20953
 
8.9%
3.0 11269
 
4.8%
0.0 7241
 
3.1%
one 6367
 
2.7%
3 5396
 
2.3%
story 4718
 
2.0%
0 4273
 
1.8%
Other values (266) 28629
12.1%
2024-05-28T12:48:38.775495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 172770
26.8%
. 155879
24.1%
1 96412
14.9%
2 80154
12.4%
3 17625
 
2.7%
e 14174
 
2.2%
o 11315
 
1.8%
9968
 
1.5%
r 8570
 
1.3%
t 8163
 
1.3%
Other values (51) 70817
11.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 645847
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 172770
26.8%
. 155879
24.1%
1 96412
14.9%
2 80154
12.4%
3 17625
 
2.7%
e 14174
 
2.2%
o 11315
 
1.8%
9968
 
1.5%
r 8570
 
1.3%
t 8163
 
1.3%
Other values (51) 70817
11.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 645847
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 172770
26.8%
. 155879
24.1%
1 96412
14.9%
2 80154
12.4%
3 17625
 
2.7%
e 14174
 
2.2%
o 11315
 
1.8%
9968
 
1.5%
r 8570
 
1.3%
t 8163
 
1.3%
Other values (51) 70817
11.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 645847
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 172770
26.8%
. 155879
24.1%
1 96412
14.9%
2 80154
12.4%
3 17625
 
2.7%
e 14174
 
2.2%
o 11315
 
1.8%
9968
 
1.5%
r 8570
 
1.3%
t 8163
 
1.3%
Other values (51) 70817
11.0%

target
Text

Distinct43926
Distinct (%)11.7%
Missing2441
Missing (%)0.6%
Memory size5.7 MiB
2024-05-28T12:48:39.360836image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length18
Median length8
Mean length7.9466593
Min length1

Characters and Unicode

Total characters2974522
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29775 ?
Unique (%)8.0%

Sample

1st row$418,000
2nd row$310,000
3rd row$2,895,000
4th row$2,395,000
5th row$5,000
ValueCountFrequency (%)
225,000 1805
 
0.5%
275,000 1648
 
0.4%
250,000 1644
 
0.4%
350,000 1639
 
0.4%
325,000 1562
 
0.4%
399,000 1547
 
0.4%
299,900 1534
 
0.4%
249,900 1500
 
0.4%
299,000 1451
 
0.4%
375,000 1440
 
0.4%
Other values (34313) 358543
95.8%
2024-05-28T12:48:40.232579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 983877
33.1%
, 418144
14.1%
9 332242
 
11.2%
$ 308456
 
10.4%
5 183472
 
6.2%
2 147630
 
5.0%
1 138693
 
4.7%
4 121445
 
4.1%
3 110212
 
3.7%
7 77907
 
2.6%
Other values (8) 152444
 
5.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2974522
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 983877
33.1%
, 418144
14.1%
9 332242
 
11.2%
$ 308456
 
10.4%
5 183472
 
6.2%
2 147630
 
5.0%
1 138693
 
4.7%
4 121445
 
4.1%
3 110212
 
3.7%
7 77907
 
2.6%
Other values (8) 152444
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2974522
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 983877
33.1%
, 418144
14.1%
9 332242
 
11.2%
$ 308456
 
10.4%
5 183472
 
6.2%
2 147630
 
5.0%
1 138693
 
4.7%
4 121445
 
4.1%
3 110212
 
3.7%
7 77907
 
2.6%
Other values (8) 152444
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2974522
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 983877
33.1%
, 418144
14.1%
9 332242
 
11.2%
$ 308456
 
10.4%
5 183472
 
6.2%
2 147630
 
5.0%
1 138693
 
4.7%
4 121445
 
4.1%
3 110212
 
3.7%
7 77907
 
2.6%
Other values (8) 152444
 
5.1%

Pool
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.2 MiB
False
336447 
True
40305 
ValueCountFrequency (%)
False 336447
89.3%
True 40305
 
10.7%
2024-05-28T12:48:40.584603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-05-28T12:48:40.764360image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Poolstate
Pool1.0000.199
state0.1991.000

Missing values

2024-05-28T12:48:12.806433image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-28T12:48:13.981485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-28T12:48:16.286174image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

statuspropertyTypestreetbathshomeFactsfireplacecityschoolssqftzipcodebedsstatestoriestargetPool
0ActiveSingle Family Home240 Heather Ln3.5{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Central A/C, Heat Pump', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': None, 'factLabel': 'lotsize'}, {'factValue': '$144', 'factLabel': 'Price/sqft'}]}Gas LogsSouthern Pines[{'rating': ['4', '4', '7', 'NR', '4', '7', 'NR', 'NR'], 'data': {'Distance': ['2.7 mi', '3.6 mi', '5.1 mi', '4.0 mi', '10.5 mi', '12.6 mi', '2.7 mi', '3.1 mi'], 'Grades': ['3–5', '6–8', '9–12', 'PK–2', '6–8', '9–12', 'PK–5', 'K–12']}, 'name': ['Southern Pines Elementary School', 'Southern Middle School', 'Pinecrest High School', 'Southern Pines Primary School', "Crain's Creek Middle School", 'Union Pines High School', 'Episcopal Day Private School', 'Calvary Christian Private School']}]2900283874NCNaN$418,000False
1for salesingle-family home12911 E Heroy Ave3 Baths{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '5828 sqft', 'factLabel': 'lotsize'}, {'factValue': '$159/sqft', 'factLabel': 'Price/sqft'}]}NaNSpokane Valley[{'rating': ['4/10', 'None/10', '4/10'], 'data': {'Distance': ['1.65mi', '1.32mi', '1.01mi'], 'Grades': ['9-12', '3-8', 'PK-8']}, 'name': ['East Valley High School&Extension', 'Eastvalley Middle School', 'Trentwood Elementary School']}]1,947 sqft992163 BedsWA2.0$310,000False
2for salesingle-family home2005 Westridge Rd2 Baths{'atAGlanceFacts': [{'factValue': '1961', 'factLabel': 'Year built'}, {'factValue': '1967', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Attached Garage', 'factLabel': 'Parking'}, {'factValue': '8,626 sqft', 'factLabel': 'lotsize'}, {'factValue': '$965/sqft', 'factLabel': 'Price/sqft'}]}yesLos Angeles[{'rating': ['8/10', '4/10', '8/10'], 'data': {'Distance': ['1.19mi', '2.06mi', '2.63mi'], 'Grades': ['6-8', 'K-5', '9-12']}, 'name': ['Paul Revere Middle School', 'Brentwood Science School', 'Palisades Charter High School']}]3,000 sqft900493 BedsCA1.0$2,895,000True
3for salesingle-family home4311 Livingston Ave8 Baths{'atAGlanceFacts': [{'factValue': '2006', 'factLabel': 'Year built'}, {'factValue': '2006', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Detached Garage', 'factLabel': 'Parking'}, {'factValue': '8,220 sqft', 'factLabel': 'lotsize'}, {'factValue': '$371/sqft', 'factLabel': 'Price/sqft'}]}yesDallas[{'rating': ['9/10', '9/10', '10/10', '9/10'], 'data': {'Distance': ['1.05mi', '0.1mi', '1.05mi', '0.81mi'], 'Grades': ['5-6', 'PK-4', '7-8', '9-12']}, 'name': ['Mcculloch Intermediate School', 'Bradfield Elementary School', 'Highland Park Middle School', 'Highland Park High School']}]6,457 sqft752055 BedsTX3.0$2,395,000False
4for salelot/land1524 Kiscoe StNaN{'atAGlanceFacts': [{'factValue': '', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '10,019 sqft', 'factLabel': 'lotsize'}, {'factValue': None, 'factLabel': 'Price/sqft'}]}NaNPalm Bay[{'rating': ['4/10', '5/10', '5/10'], 'data': {'Distance': ['5.96mi', '3.25mi', '3.03mi'], 'Grades': ['7-8', '9-12', 'PK-6']}, 'name': ['Southwest Middle School', 'Bayside High School', 'Westside Elementary School']}]NaN32908NaNFLNaN$5,000False
5for saletownhouse1624 S Newkirk StNaN{'atAGlanceFacts': [{'factValue': '1920', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '680 sqft', 'factLabel': 'lotsize'}, {'factValue': '$233/sqft', 'factLabel': 'Price/sqft'}]}NaNPhiladelphia[{'rating': [], 'data': {'Distance': [], 'Grades': []}, 'name': []}]897 sqft191452 BedsPA2.0$209,000False
6ActiveFlorida552 Casanova CtNaN{'atAGlanceFacts': [{'factValue': '2006', 'factLabel': 'Year built'}, {'factValue': '2006', 'factLabel': 'Remodeled year'}, {'factValue': 'Electric, Heat Pump', 'factLabel': 'Heating'}, {'factValue': 'Central Air', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '4,996 Sq. Ft.', 'factLabel': 'lotsize'}, {'factValue': '$120 / Sq. Ft.', 'factLabel': 'Price/sqft'}]}NaNPOINCIANA[{'rating': ['3', '3', '1', 'NR'], 'data': {'Distance': ['0.8 mi', '8.3 mi', '4.2 mi', '2.0 mi'], 'Grades': ['Preschool to 4', 'Preschool to 12', '5 to 8', '1 to 12']}, 'name': ['Palmetto Elementary School', 'Haines City Senior High School', 'Lake Marion Creek Elementary School', 'Chosen Generation Christian Academy']}]1,50734759NaNFLOne181,500False
7ActiveNaN6094 Mingle DrNaN{'atAGlanceFacts': [{'factValue': '1976', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '8,750 Sq. Ft.', 'factLabel': 'lotsize'}, {'factValue': '$57 / Sq. Ft.', 'factLabel': 'Price/sqft'}]}NaNMemphis[{'rating': ['4', '2', '2'], 'data': {'Distance': ['0.7 mi', '0.4 mi', '2.2 mi'], 'Grades': ['Preschool to 5', '6 to 8', '9 to 12']}, 'name': ['Crump Elementary School', 'Hickory Ridge Middle School', 'Wooddale High School']}]NaN38115NaNTNNaN68,000False
8ActiveSingle Family Home11182 Owl Ave2{'atAGlanceFacts': [{'factValue': '1970', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '124582', 'factLabel': 'lotsize'}, {'factValue': '$68', 'factLabel': 'Price/sqft'}]}NaNMason City[{'rating': ['2', '2', '4', '7', '4', 'NR'], 'data': {'Distance': ['5.6 mi', '5.6 mi', '6.8 mi', '6.5 mi', '6.8 mi', '6.8 mi'], 'Grades': ['PK–4', '5–6', '9–12', 'PK–4', '7–8', '9–12']}, 'name': ['Roosevelt Elementary School', 'Lincoln Intermediate School', 'Mason City High School', 'Jefferson Elementary School', 'John Adams Middle School', 'Alternative School']}]3588504013IANaN$244,900False
9NaNSingle Family8612 Cedar Plains Ln3{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': 'Gas', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Attached Garage', 'factLabel': 'Parking'}, {'factValue': '2,056 sqft', 'factLabel': 'lotsize'}, {'factValue': '$162', 'factLabel': 'Price/sqft'}]}NaNHouston[{'rating': ['4/10', '3/10', '2/10'], 'data': {'Distance': ['0.7 mi', '0.6 mi', '1.9 mi'], 'Grades': ['PK-5', '5-8', '9-12']}, 'name': ['Edgewood Elementary School', 'Landrum Middle School', 'Northbrook High School']}]1,930770803TX2.0$311,995False
statuspropertyTypestreetbathshomeFactsfireplacecityschoolssqftzipcodebedsstatestoriestargetPool
377034for salesingle-family home9711 Lawngate Dr3 Baths{'atAGlanceFacts': [{'factValue': '1970', 'factLabel': 'Year built'}, {'factValue': '1970', 'factLabel': 'Remodeled year'}, {'factValue': 'Other', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Detached Garage', 'factLabel': 'Parking'}, {'factValue': '6,599 sqft', 'factLabel': 'lotsize'}, {'factValue': '$156/sqft', 'factLabel': 'Price/sqft'}]}yesHouston[{'rating': ['2/10', '3/10', '3/10'], 'data': {'Distance': ['0.65mi', '1.15mi', '0.19mi'], 'Grades': ['9-12', 'PK-5', '6-8']}, 'name': ['Northbrook High School', 'Terrace Elementary School', 'Northbrook Middle School']}]1,792 sqft770804 BedsTX2.0$280,000False
377035NaNSingle Family3263 Wolcott Pl2.0{'atAGlanceFacts': [{'factValue': '1962', 'factLabel': 'Year built'}, {'factValue': '1967', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '1 space', 'factLabel': 'Parking'}, {'factValue': '7,704 sqft', 'factLabel': 'lotsize'}, {'factValue': None, 'factLabel': 'Price/sqft'}]}YesOrlando[{'rating': ['3/10', '1/10', '3/10'], 'data': {'Distance': ['1.5 mi', '1.3 mi', '1.1 mi'], 'Grades': ['PK-5', '6-8', '9-12']}, 'name': ['Washington Shores Elementary School', 'Carver Middle School', 'Jones High School']}]1,829 sqft328053FL1$171,306False
377036ActiveSingle Detached, Traditional2805 S Jennings AveNaN{'atAGlanceFacts': [{'factValue': '1921', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': 'Central A/C (Electric), Central Heat (Electric)', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '7,500 Sq. Ft.', 'factLabel': 'lotsize'}, {'factValue': '$105 / Sq. Ft.', 'factLabel': 'Price/sqft'}]}NaNFort Worth[{'rating': ['4', '6', '5'], 'data': {'Distance': ['0.5 mi', '2.0 mi', '1.3 mi'], 'Grades': ['Preschool to 5', '6 to 8', '9 to 12']}, 'name': ['Daggett Elementary School', 'Rosemont Middle School', 'Paschal High School']}]1,89576110NaNTXNaN199,900False
377037NaNSingle FamilyBuildable plan: The Torino (384L) Riverstone Ranch - Premier2{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': 'No Data', 'factLabel': 'Heating'}, {'factValue': 'No Data', 'factLabel': 'Cooling'}, {'factValue': '2 spaces', 'factLabel': 'Parking'}, {'factValue': 'No Data', 'factLabel': 'lotsize'}, {'factValue': '$137', 'factLabel': 'Price/sqft'}]}NaNHouston[{'rating': ['7/10', '6/10', '5/10'], 'data': {'Distance': ['0.3 mi', '2.5 mi', '2.5 mi'], 'Grades': ['PK-4', '7-8', '9-12']}, 'name': ['South Belt Elementary School', 'Thompson Intermediate School', 'Dobie High School']}]1,841770894TX1.0$252,990False
377038For saleCondo2238 11th St NW APT 23{'atAGlanceFacts': [{'factValue': '2010', 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': 'Forced air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '1 space', 'factLabel': 'Parking'}, {'factValue': None, 'factLabel': 'lotsize'}, {'factValue': '$564', 'factLabel': 'Price/sqft'}]}NaNWashington[{'rating': ['3/10', '3/10'], 'data': {'Distance': ['0.4 mi', '0.1 mi'], 'Grades': ['PK-5', '6-12']}, 'name': ['Garrison Elementary School', 'Cardozo Education Campus']}]1,417200012DC3.0$799,000False
377039NaNSingle Family20800 NE 23rd Ave6.0{'atAGlanceFacts': [{'factValue': '1990', 'factLabel': 'Year built'}, {'factValue': '1990', 'factLabel': 'Remodeled year'}, {'factValue': 'Other', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '2 spaces', 'factLabel': 'Parking'}, {'factValue': '8,500 sqft', 'factLabel': 'lotsize'}, {'factValue': '$311', 'factLabel': 'Price/sqft'}]}NaNMiami[{'rating': ['10/10', '5/10'], 'data': {'Distance': ['32.1 mi', '1.1 mi'], 'Grades': ['PK-8', '9-12']}, 'name': ['Air Base Elementary School', 'Dr Michael M. Krop Senior High School']}]4,017331805FL0.0$1,249,000True
377040for salecondo3530 N Lake Shore Dr #4B3 Baths{'atAGlanceFacts': [{'factValue': '1924', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Radiant', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': 'None', 'factLabel': 'Parking'}, {'factValue': '', 'factLabel': 'lotsize'}, {'factValue': '$337/sqft', 'factLabel': 'Price/sqft'}]}NaNChicago[{'rating': ['1/10', '5/10', '7/10'], 'data': {'Distance': ['10.61mi', '1.42mi', '0.4mi'], 'Grades': ['9-12', '9-12', 'PK-8']}, 'name': ['Hope College Prep High School', 'Lake View High School', 'Nettelhorst Elementary School']}]2,000 sqft606573 BedsIL9.0$674,999False
377041for salesingle-family home15509 Linden Blvd3 Baths{'atAGlanceFacts': [{'factValue': '1950', 'factLabel': 'Year built'}, {'factValue': '1950', 'factLabel': 'Remodeled year'}, {'factValue': 'Other', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '2', 'factLabel': 'Parking'}, {'factValue': '1,600 sqft', 'factLabel': 'lotsize'}, {'factValue': '$458/sqft', 'factLabel': 'Price/sqft'}]}NaNJamaica[{'rating': ['5/10', '4/10'], 'data': {'Distance': ['0.48mi', '0.73mi'], 'Grades': ['PK-5', '6-8']}, 'name': ['Ps 48 William Wordsworth', 'Jhs 8 Richard S Grossley']}]1,152 sqft114343 BedsNY2$528,000False
377042NaNNaN7810 Pereida StNaN{'atAGlanceFacts': [{'factValue': None, 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': None, 'factLabel': 'Heating'}, {'factValue': None, 'factLabel': 'Cooling'}, {'factValue': None, 'factLabel': 'Parking'}, {'factValue': None, 'factLabel': 'lotsize'}, {'factValue': None, 'factLabel': 'Price/sqft'}]}NaNHouston[{'rating': ['NA', 'NA', 'NA'], 'data': {'Distance': ['1.3 mi', '0.5 mi', '1.9 mi'], 'Grades': ['PK-5', '6-8', '9-12']}, 'name': ['Hiliard El', 'Forest Brook Middle', 'North Forest High School']}]NaN770288,479 sqftTXNaN$34,500False
377043NaNSingle Family5983 Midcrown Dr2.0{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': 'Electric', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'No Data', 'factLabel': 'Parking'}, {'factValue': '6,969 sqft', 'factLabel': 'lotsize'}, {'factValue': '$140', 'factLabel': 'Price/sqft'}]}Not ApplicableSan Antonio[{'rating': ['5/10', '4/10', '3/10'], 'data': {'Distance': ['0.3 mi', '1.1 mi', '4.1 mi'], 'Grades': ['PK-5', '6-8', '9-12']}, 'name': ['Mary Lou Hartman', 'Woodlake Hills Middle School', 'Judson High School']}]1,462782183TX1.0$204,900False